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Understanding the Normal Distribution is crucial as it is the most important and most widely used distribution in statistics. In this Statistics Tutorial, we are going to introduce one of the most commonly found continuous distributions – the normal distribution. For starters, we will define what types of events follow a Normal Distribution, and then we will examine some of its distinct characteristics.

Download the Standard Normal Distribution working file:
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We define a Normal Distribution using a capital letter N followed by the mean and variance of the distribution. We read the following notation as “Variable “X” follows a Normal Distribution with mean “mu” and variance “sigma” squared”.

When dealing with actual data we would usually know the numerical values of mu and sigma squared.

The normal distribution frequently appears in nature, as well as in life, in various shapes of forms. For example, the size of a full-grown male lion follows a normal distribution. Many records suggest that the average lion weight between 150 and 250 kilograms, or 330 to 550 pounds. Of course, there exist specimen which fall outside of this range. Lions weighing less than 150, or more than 250 kilograms tend to be the exception rather than the rule.

Such individuals serve as outliers in our set and the more data we gather, the lower part of the data they represent!

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